Senior Engineering Manager, Data Platform and AI

About Lucid

At Lucid we are creating exceptional mobility experiences through innovation to drive the world forward. Built on Lucids proprietary technology and software-defined vehicle architecture our award-winning vehicles bring our Compromise Nothing approach to the global automotive market. That means refusing to choose between performance and sustainability design and engineering ambition and Lucid Air and Lucid Gravity we have designed and built vehicles that have redefined their segments combining exceptional range performance design and expansive space in a single experience.

We achieve this through deep vertical integration with design engineering and productionhappening in-houseacross our global offices the world united by a shared commitment to refusing to settle youcanhelpredefinewhatspossible andshape the future of mobility.

We are seeking an experienced Senior Engineering Manager Data Platform and AI to lead the strategy architecture delivery and operation of an enterprise data platform that ingests high-volume vehicle telemetry and enterprise systems data integrates and curates it into trusted data products and provides scalable governed AI-ready data foundations. This role will oversee teams building business-critical capabilities for engineering manufacturing supply chain finance sales service and corporate functions.

The ideal candidate combines strong engineering leadership with deep technical expertise in data engineering data quality AWS and Amazon Redshift. You will build and lead a high-performing team responsible for reliable batch and streaming ingestion cross-domain data integration identity resolution data curation governance and platform operations at scale.

• Define and execute the strategy and roadmap for enterprise data telemetry and AI platforms.
• Lead mentor and grow a high-performing team of data and platform engineers.
• Drive engineering excellence through automation operational rigor and modern development practices.
• Partner with business and technology leaders to deliver high-impact data products and capabilities.

• Own the architecture reliability performance security and cost efficiency of the enterprise data platform on AWS.
• Lead the design and operation of Amazon Redshift including data modeling distribution and sort strategies workload management scaling performance tuning access controls and cost optimization.
• Develop and operate scalable data lakes warehouses streaming platforms orchestration frameworks and self-service data capabilities.
• Establish reusable platform patterns data contracts metadata standards and automation that improve delivery speed and operational consistency.

• Build and operate high-volume resilient batch and real-time pipelines that ingest vehicle telemetry and data from enterprise applications.
• Integrate and stitch telemetry with manufacturing supply chain sales service finance customer and master data to create consistent cross-domain views.
• Address schema evolution late-arriving events time-series processing event ordering data contracts and vehicle-to-enterprise identity resolution.
• Curate governed reusable data products and standardized business entities that support analytics engineering diagnostics machine learning and Generative AI.
• Provide secure reliable self-service access to trusted telemetry and enterprise data for engineering data science and business teams.

• Define and enforce data quality standards ownership controls and measurable SLAs across critical data products.
• Implement data profiling validation reconciliation lineage observability anomaly detection and root-cause remediation capabilities.
• Establish monitoring incident management disaster recovery and service-level objectives for business-critical data services.
• Lead platform modernization performance optimization security compliance and cloud cost optimization initiatives.

• Bachelors or Masters degree in Computer Science Engineering Data Science or a related field.
• 12 years of experience in data engineering data platform engineering distributed systems or large-scale data technologies.
• 6 years of experience leading engineering teams and delivering enterprise-scale production data solutions.
• Deep hands-on expertise in Amazon Redshift including dimensional modeling distribution and sort strategies workload management query and storage optimization security scaling and cost management.
• Proven experience integrating high-volume vehicle IoT connected-product or telemetry data with enterprise transactional and master data.
• Strong knowledge of data quality management including profiling validation reconciliation lineage observability quality metrics and remediation processes.
• Experience creating curated governed reusable data products and AI-ready datasets for analytics machine learning and Generative AI.
• Deep understanding of batch and streaming architectures schema evolution event processing time-series data data contracts and distributed data systems.
• Strong AWS experience and hands-on knowledge of technologies such as S3 Glue Lambda Kinesis or Kafka Airflow Spark IAM Terraform CI/CD and observability platforms.
• Strong programming skills in Python and SQL with experience in Java and/or Scala preferred.
• Strong software engineering foundation and experience operating secure reliable petabyte-scale data platforms in production.
• Excellent communication and stakeholder management skills with the ability to translate business and AI use cases into scalable technical solutions.